---

title: Python date: 2020-12-23 18:41:20 background: bg-[#436b97] tags: - script - interpret - 编程语言 - 后端开发 categories: - Programming intro: | Python 速查表 - 包含 Python 3 编程语言最重要的概念、语法和常用方法。适合初学者和开发者快速参考。 plugins: - copyCode - runCode

入门指南 {.cols-3}

简介

Python 是一种高级、解释型、动态类型的编程语言，以简洁易读著称。

• Python 官网 (python.org)
• Python 官方文档 (docs.python.org)
• Python 中文文档 (docs.python.org/zh-cn)
• Python 正则表达式 (cheatsheets)

Hello World

# 最简单的 Python 程序
print("Hello, World!")

# 使用 f-string 格式化输出
name = "Python"
print(f"Hello, {name}!")

Python 程序从上到下执行，不需要 main 函数

变量声明

# Python 是动态类型语言，无需声明类型
age = 18          # 整数 int
name = "张三"     # 字符串 str
price = 99.99     # 浮点数 float
is_valid = True   # 布尔值 bool

# 多变量赋值
x, y, z = 1, 2, 3
a = b = c = 0     # 相同值赋给多个变量

# 变量命名规则：字母/下划线开头，区分大小写
user_name = "admin"  # 推荐使用下划线命名法

数据类型 {.row-span-2}

# 类型检查
type(42)        # <class 'int'>
type("hello")   # <class 'str'>

# 类型判断
isinstance(42, int)      # True
isinstance("hi", str)    # True

字符串切片

text = "Hello, World!"

# 基本切片 [start:end:step]
text[0:5]      # 'Hello' (索引0-4)
text[7:]       # 'World!' (从索引7到末尾)
text[:5]       # 'Hello' (从开头到索引4)
text[-6:-1]    # 'World' (负索引)
text[::2]      # 'Hlo ol!' (每隔一个字符)
text[::-1]     # '!dlroW ,olleH' (反转)

列表操作

# 创建列表
fruits = ["apple", "banana", "cherry"]
numbers = list(range(1, 6))  # [1, 2, 3, 4, 5]

# 常用操作
fruits.append("orange")     # 末尾添加
fruits.insert(0, "grape")   # 指定位置插入
fruits.remove("banana")     # 删除元素
fruits.pop()                # 删除并返回最后一个
len(fruits)                 # 获取长度

# 列表推导式 (List Comprehension)
squares = [x**2 for x in range(10)]
evens = [x for x in range(20) if x % 2 == 0]

条件语句

score = 85

if score >= 90:
    grade = "A"
elif score >= 80:
    grade = "B"
elif score >= 70:
    grade = "C"
else:
    grade = "D"

# 三元运算符
result = "及格" if score >= 60 else "不及格"

# match-case (Python 3.10+)
match score // 10:
    case 10 | 9:
        grade = "A"
    case 8:
        grade = "B"
    case _:
        grade = "C"

循环语句

# for 循环
for i in range(5):
    print(i)  # 0, 1, 2, 3, 4

# 遍历列表
fruits = ["apple", "banana"]
for fruit in fruits:
    print(fruit)

# 带索引遍历
for i, fruit in enumerate(fruits):
    print(f"{i}: {fruit}")

# while 循环
count = 0
while count < 5:
    print(count)
    count += 1

# break 和 continue
for i in range(10):
    if i == 3:
        continue  # 跳过本次循环
    if i == 7:
        break     # 退出循环
    print(i)

函数定义

# 基本函数
def greet(name):
    """问候函数 - 这是文档字符串"""
    return f"Hello, {name}!"

# 默认参数
def power(base, exp=2):
    return base ** exp

# 可变参数
def sum_all(*args):
    return sum(args)

# 关键字参数
def create_user(**kwargs):
    return kwargs

# Lambda 表达式
square = lambda x: x ** 2
add = lambda x, y: x + y

文件操作 {.col-span-2}

# 读取文件
with open("file.txt", "r", encoding="utf-8") as f:
    content = f.read()        # 读取全部内容
    # 或逐行读取
    # for line in f:
    #     print(line.strip())

# 写入文件
with open("file.txt", "w", encoding="utf-8") as f:
    f.write("Hello, World!")

# 追加内容
with open("file.txt", "a", encoding="utf-8") as f:
    f.write("\n新的一行")

# JSON 文件操作
import json
with open("data.json", "w") as f:
    json.dump({"name": "张三", "age": 25}, f, ensure_ascii=False)

with open("data.json", "r") as f:
    data = json.load(f)

使用 with 语句可以自动关闭文件，避免资源泄露

算术运算符

a, b = 10, 3

a + b    # 13 加法
a - b    # 7  减法
a * b    # 30 乘法
a / b    # 3.333... 除法(返回浮点数)
a // b   # 3  整除(向下取整)
a % b    # 1  取余
a ** b   # 1000 幂运算

# 复合赋值运算符
x = 10
x += 5   # x = x + 5 -> 15
x -= 3   # x = x - 3 -> 12
x *= 2   # x = x * 2 -> 24

字符串操作 {.cols-2}

字符串方法

s = "  Hello, World!  "

# 大小写转换
s.upper()          # "  HELLO, WORLD!  "
s.lower()          # "  hello, world!  "
s.title()          # "  Hello, World!  "
s.capitalize()     # "  hello, world!  "

# 去除空白
s.strip()          # "Hello, World!"
s.lstrip()         # "Hello, World!  "
s.rstrip()         # "  Hello, World!"

# 查找替换
s.find("World")    # 9 (返回索引，未找到返回-1)
s.index("World")   # 9 (未找到抛出异常)
s.replace("World", "Python")  # "  Hello, Python!  "
s.count("l")       # 3

# 判断方法
s.startswith("  H")  # True
s.endswith("!  ")    # True
"hello".isalpha()    # True (全是字母)
"123".isdigit()      # True (全是数字)
"hello123".isalnum() # True (字母或数字)

字符串格式化

name = "张三"
age = 25
price = 99.5

# f-string (推荐，Python 3.6+)
f"姓名: {name}, 年龄: {age}"
f"价格: {price:.2f}"      # 保留2位小数
f"数字: {42:08d}"         # 补零: 00000042
f"百分比: {0.85:.1%}"     # 百分比: 85.0%

# format 方法
"姓名: {}, 年龄: {}".format(name, age)
"姓名: {n}, 年龄: {a}".format(n=name, a=age)

# % 格式化 (旧式)
"姓名: %s, 年龄: %d" % (name, age)
"价格: %.2f" % price

# 对齐
f"{'左对齐':<10}"   # '左对齐       '
f"{'右对齐':>10}"   # '       右对齐'
f"{'居中':^10}"     # '    居中    '

字符串分割与连接

# 分割
text = "apple,banana,cherry"
fruits = text.split(",")      # ['apple', 'banana', 'cherry']

text2 = "hello world python"
words = text2.split()         # ['hello', 'world', 'python']

# 按行分割
lines = "line1\nline2\nline3".splitlines()

# 连接
"-".join(["a", "b", "c"])     # "a-b-c"
" ".join(words)               # "hello world python"
"".join(["H", "i"])           # "Hi"

多行字符串

# 三引号字符串
text = """这是一个
多行字符串，
可以保留换行符。"""

# 原始字符串 (忽略转义)
path = r"C:\Users\name\Documents"

# 字节字符串
data = b"Hello"
type(data)  # <class 'bytes'>

列表与元组 {.cols-2}

列表方法 {.row-span-2}

lst = [3, 1, 4, 1, 5, 9, 2, 6]

# 添加元素
lst.append(7)           # 末尾添加 [3,1,4,1,5,9,2,6,7]
lst.insert(0, 0)        # 指定位置插入
lst.extend([8, 9])      # 扩展列表

# 删除元素
lst.remove(1)           # 删除第一个匹配的元素
lst.pop()               # 删除并返回最后一个元素
lst.pop(0)              # 删除并返回指定索引的元素
lst.clear()             # 清空列表

# 查找
lst = [3, 1, 4, 1, 5]
lst.index(4)            # 2 (返回第一个匹配的索引)
lst.count(1)            # 2 (统计出现次数)
4 in lst                # True (是否存在)

# 排序
lst.sort()              # 原地排序 [1, 1, 3, 4, 5]
lst.sort(reverse=True)  # 降序排序
sorted(lst)             # 返回新列表，不修改原列表
lst.reverse()           # 原地反转

# 复制
lst2 = lst.copy()       # 浅拷贝
lst3 = lst[:]           # 切片复制
import copy
lst4 = copy.deepcopy(lst)  # 深拷贝

列表推导式

# 基本语法: [表达式 for 变量 in 可迭代对象 if 条件]

# 平方数列表
squares = [x**2 for x in range(10)]
# [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

# 带条件过滤
evens = [x for x in range(20) if x % 2 == 0]
# [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]

# 嵌套循环
matrix = [[i*j for j in range(1,4)] for i in range(1,4)]
# [[1,2,3], [2,4,6], [3,6,9]]

# 字典推导式
squares_dict = {x: x**2 for x in range(5)}
# {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

# 集合推导式
unique_lengths = {len(word) for word in ["hello", "world", "hi"]}
# {2, 5}

元组操作

# 创建元组 (不可变)
t1 = (1, 2, 3)
t2 = 1, 2, 3          # 括号可省略
t3 = tuple([1, 2, 3])
t4 = (1,)             # 单元素元组需要逗号

# 元组解包
a, b, c = (1, 2, 3)
first, *rest = (1, 2, 3, 4)  # first=1, rest=[2,3,4]
a, *middle, z = (1, 2, 3, 4, 5)  # middle=[2,3,4]

# 元组方法
t = (1, 2, 3, 2, 1)
t.count(2)    # 2
t.index(3)    # 2

# 元组与列表转换
list((1, 2, 3))   # [1, 2, 3]
tuple([1, 2, 3])  # (1, 2, 3)

元组是不可变的，适合存储不应被修改的数据

切片操作

lst = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

# 基本切片 [start:end:step]
lst[2:5]      # [2, 3, 4]
lst[:3]       # [0, 1, 2]
lst[7:]       # [7, 8, 9]
lst[::2]      # [0, 2, 4, 6, 8] 每隔一个
lst[::-1]     # [9, 8, 7, 6, 5, 4, 3, 2, 1, 0] 反转

# 负索引
lst[-3:]      # [7, 8, 9]
lst[:-3]      # [0, 1, 2, 3, 4, 5, 6]
lst[-5:-2]    # [5, 6, 7]

# 切片赋值
lst[2:5] = [20, 30, 40]
lst[::2] = [0, 0, 0, 0, 0]  # 必须长度匹配

字典与集合 {.cols-2}

字典操作 {.row-span-2}

# 创建字典
d1 = {"name": "张三", "age": 25}
d2 = dict(name="李四", age=30)
d3 = dict([("a", 1), ("b", 2)])

# 访问元素
d1["name"]          # "张三"
d1.get("name")      # "张三"
d1.get("city", "未知")  # "未知" (默认值)

# 添加/修改
d1["city"] = "北京"
d1.update({"age": 26, "job": "工程师"})

# 删除
del d1["age"]
d1.pop("city")      # 删除并返回
d1.popitem()        # 删除并返回最后一项 (Python 3.7+)
d1.clear()          # 清空

# 常用方法
d = {"a": 1, "b": 2, "c": 3}
d.keys()            # dict_keys(['a', 'b', 'c'])
d.values()          # dict_values([1, 2, 3])
d.items()           # dict_items([('a',1), ('b',2), ('c',3)])

# 遍历字典
for key in d:
    print(key, d[key])

for key, value in d.items():
    print(f"{key}: {value}")

# 字典推导式
squares = {x: x**2 for x in range(5)}

集合操作

# 创建集合 (无序、不重复)
s1 = {1, 2, 3, 4, 5}
s2 = set([3, 4, 5, 6, 7])
s3 = set()  # 空集合 (不能用 {})

# 添加/删除
s1.add(6)
s1.remove(1)    # 不存在会报错
s1.discard(10)  # 不存在不会报错
s1.pop()        # 随机删除一个
s1.clear()      # 清空

# 集合运算
a = {1, 2, 3, 4}
b = {3, 4, 5, 6}

a | b    # 并集 {1, 2, 3, 4, 5, 6}
a & b    # 交集 {3, 4}
a - b    # 差集 {1, 2}
a ^ b    # 对称差集 {1, 2, 5, 6}

# 集合方法
a.union(b)
a.intersection(b)
a.difference(b)
a.symmetric_difference(b)

# 子集判断
{1, 2}.issubset({1, 2, 3})      # True
{1, 2, 3}.issuperset({1, 2})    # True

默认字典与计数器

from collections import defaultdict, Counter

# defaultdict - 带默认值的字典
dd = defaultdict(list)
dd["fruits"].append("apple")
dd["fruits"].append("banana")
# {'fruits': ['apple', 'banana']}

dd2 = defaultdict(int)
dd2["count"] += 1  # 自动初始化为 0

# Counter - 计数器
words = ["apple", "banana", "apple", "cherry", "banana", "apple"]
counter = Counter(words)
# Counter({'apple': 3, 'banana': 2, 'cherry': 1})

counter.most_common(2)  # [('apple', 3), ('banana', 2)]
counter["apple"]        # 3

嵌套数据结构

# 嵌套字典
users = {
    "user1": {"name": "张三", "age": 25, "skills": ["Python", "Java"]},
    "user2": {"name": "李四", "age": 30, "skills": ["JavaScript", "React"]}
}

# 访问嵌套数据
users["user1"]["name"]        # "张三"
users["user1"]["skills"][0]   # "Python"

# 嵌套列表 (矩阵)
matrix = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]
matrix[1][2]  # 6

# 安全访问嵌套数据
def safe_get(d, *keys, default=None):
    for key in keys:
        if isinstance(d, dict):
            d = d.get(key, default)
        else:
            return default
    return d

safe_get(users, "user1", "name")  # "张三"
safe_get(users, "user3", "name", default="未知")  # "未知"

函数进阶 {.cols-2}

参数类型 {.row-span-2}

# 位置参数
def greet(name, greeting):
    return f"{greeting}, {name}!"

# 默认参数
def greet(name, greeting="Hello"):
    return f"{greeting}, {name}!"

# 关键字参数
greet(name="张三", greeting="你好")

# *args - 可变位置参数
def sum_all(*args):
    return sum(args)
sum_all(1, 2, 3, 4)  # 10

# **kwargs - 可变关键字参数
def print_info(**kwargs):
    for key, value in kwargs.items():
        print(f"{key}: {value}")
print_info(name="张三", age=25)

# 混合使用
def func(a, b, *args, c=10, **kwargs):
    print(f"a={a}, b={b}, args={args}, c={c}, kwargs={kwargs}")

# 仅限关键字参数 (Python 3)
def func(a, b, *, c, d):  # c 和 d 必须用关键字传递
    pass

# 仅限位置参数 (Python 3.8+)
def func(a, b, /, c, d):  # a 和 b 必须用位置传递
    pass

Lambda 表达式

# 基本语法: lambda 参数: 表达式
square = lambda x: x ** 2
add = lambda x, y: x + y

# 常见用法
numbers = [1, 2, 3, 4, 5]

# 配合 map
list(map(lambda x: x**2, numbers))  # [1, 4, 9, 16, 25]

# 配合 filter
list(filter(lambda x: x % 2 == 0, numbers))  # [2, 4]

# 配合 sorted
students = [("Alice", 85), ("Bob", 90), ("Charlie", 78)]
sorted(students, key=lambda x: x[1], reverse=True)
# [('Bob', 90), ('Alice', 85), ('Charlie', 78)]

# 配合 reduce
from functools import reduce
reduce(lambda x, y: x + y, numbers)  # 15

装饰器

# 基本装饰器
def my_decorator(func):
    def wrapper(*args, **kwargs):
        print("函数执行前")
        result = func(*args, **kwargs)
        print("函数执行后")
        return result
    return wrapper

@my_decorator
def say_hello(name):
    print(f"Hello, {name}!")

# 带参数的装饰器
def repeat(times):
    def decorator(func):
        def wrapper(*args, **kwargs):
            for _ in range(times):
                result = func(*args, **kwargs)
            return result
        return wrapper
    return decorator

@repeat(3)
def greet(name):
    print(f"Hello, {name}!")

# 保留函数元数据
from functools import wraps

def my_decorator(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        return func(*args, **kwargs)
    return wrapper

生成器

# 生成器函数 (使用 yield)
def countdown(n):
    while n > 0:
        yield n
        n -= 1

for num in countdown(5):
    print(num)  # 5, 4, 3, 2, 1

# 生成器表达式
squares = (x**2 for x in range(10))  # 注意是圆括号
for s in squares:
    print(s)

# 无限生成器
def infinite_sequence():
    num = 0
    while True:
        yield num
        num += 1

# 生成器方法
gen = (x for x in range(3))
next(gen)  # 0
next(gen)  # 1

生成器是惰性求值的，适合处理大数据

类与面向对象 {.cols-2}

类定义 {.row-span-2}

class Person:
    # 类变量
    species = "Human"

    # 构造方法
    def __init__(self, name, age):
        # 实例变量
        self.name = name
        self.age = age

    # 实例方法
    def greet(self):
        return f"Hello, I'm {self.name}"

    # 类方法
    @classmethod
    def create_anonymous(cls):
        return cls("Anonymous", 0)

    # 静态方法
    @staticmethod
    def is_adult(age):
        return age >= 18

    # 属性装饰器
    @property
    def info(self):
        return f"{self.name}, {self.age}岁"

    # 字符串表示
    def __str__(self):
        return f"Person({self.name}, {self.age})"

    def __repr__(self):
        return f"Person('{self.name}', {self.age})"

# 使用
p = Person("张三", 25)
p.greet()                    # "Hello, I'm 张三"
p.info                       # "张三, 25岁"
Person.is_adult(20)          # True
Person.create_anonymous()    # Person('Anonymous', 0)

继承

class Animal:
    def __init__(self, name):
        self.name = name

    def speak(self):
        raise NotImplementedError("子类必须实现此方法")

class Dog(Animal):
    def speak(self):
        return f"{self.name} says Woof!"

    def fetch(self):
        return f"{self.name} is fetching!"

class Cat(Animal):
    def speak(self):
        return f"{self.name} says Meow!"

# 多重继承
class FlyingMixin:
    def fly(self):
        return f"{self.name} is flying!"

class Bird(Animal, FlyingMixin):
    def speak(self):
        return f"{self.name} says Tweet!"

# 使用
dog = Dog("Buddy")
dog.speak()   # "Buddy says Woof!"
dog.fetch()   # "Buddy is fetching!"

bird = Bird("Tweety")
bird.fly()    # "Tweety is flying!"

# 调用父类方法
class Child(Parent):
    def __init__(self, name, extra):
        super().__init__(name)
        self.extra = extra

魔术方法

class Vector:
    def __init__(self, x, y):
        self.x = x
        self.y = y

    # 加法运算符
    def __add__(self, other):
        return Vector(self.x + other.x, self.y + other.y)

    # 相等比较
    def __eq__(self, other):
        return self.x == other.x and self.y == other.y

    # 长度
    def __len__(self):
        return 2

    # 索引访问
    def __getitem__(self, index):
        return [self.x, self.y][index]

    # 字符串表示
    def __str__(self):
        return f"Vector({self.x}, {self.y})"

    # 可调用
    def __call__(self):
        return (self.x, self.y)

v1 = Vector(1, 2)
v2 = Vector(3, 4)
v3 = v1 + v2      # Vector(4, 6)
v1 == v2          # False
len(v1)           # 2
v1[0]             # 1
v1()              # (1, 2)

数据类 (Python 3.7+)

from dataclasses import dataclass, field
from typing import List

@dataclass
class Student:
    name: str
    age: int
    grades: List[int] = field(default_factory=list)

    # 自动生成 __init__, __repr__, __eq__

    def average_grade(self):
        return sum(self.grades) / len(self.grades) if self.grades else 0

# 使用
s1 = Student("张三", 20, [85, 90, 78])
s2 = Student("李四", 21)

print(s1)  # Student(name='张三', age=20, grades=[85, 90, 78])
s1.average_grade()  # 84.33...

# 不可变数据类
@dataclass(frozen=True)
class Point:
    x: float
    y: float

p = Point(1.0, 2.0)
# p.x = 3.0  # 会报错

异常处理 {.cols-2}

try-except 语句

try:
    result = 10 / 0
except ZeroDivisionError:
    print("不能除以零")
except (TypeError, ValueError) as e:
    print(f"类型或值错误: {e}")
except Exception as e:
    print(f"其他错误: {e}")
else:
    print("没有异常时执行")
finally:
    print("无论如何都会执行")

# 简洁写法
try:
    risky_operation()
except SomeError:
    pass  # 忽略错误

自定义异常

# 定义自定义异常
class ValidationError(Exception):
    """验证错误"""
    pass

class InsufficientFundsError(Exception):
    """余额不足错误"""
    def __init__(self, balance, amount):
        self.balance = balance
        self.amount = amount
        super().__init__(
            f"余额不足: 当前余额 {balance}, 需要 {amount}"
        )

# 使用
def withdraw(balance, amount):
    if amount > balance:
        raise InsufficientFundsError(balance, amount)
    return balance - amount

try:
    withdraw(100, 150)
except InsufficientFundsError as e:
    print(e.balance, e.amount)

上下文管理器

# 使用 with 语句
with open("file.txt") as f:
    content = f.read()
# 文件自动关闭

# 自定义上下文管理器 (类方式)
class Timer:
    def __enter__(self):
        import time
        self.start = time.time()
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        import time
        self.end = time.time()
        print(f"耗时: {self.end - self.start:.2f}秒")
        return False  # 不抑制异常

with Timer():
    # 计时代码
    sum(range(1000000))

# 使用 contextlib (函数方式)
from contextlib import contextmanager

@contextmanager
def timer():
    import time
    start = time.time()
    yield
    print(f"耗时: {time.time() - start:.2f}秒")

断言

# 断言 (调试用)
def divide(a, b):
    assert b != 0, "除数不能为零"
    return a / b

# 在生产环境可以用 python -O 禁用断言
# assert 只用于调试，不要用于输入验证

# 正确的输入验证
def divide_safe(a, b):
    if b == 0:
        raise ValueError("除数不能为零")
    return a / b

常用模块 {.cols-2}

datetime 日期时间

from datetime import datetime, date, time, timedelta

# 当前时间
now = datetime.now()
today = date.today()

# 创建日期时间
dt = datetime(2024, 1, 15, 10, 30, 0)
d = date(2024, 1, 15)
t = time(10, 30, 0)

# 格式化
now.strftime("%Y-%m-%d %H:%M:%S")  # "2024-01-15 10:30:00"
now.strftime("%Y年%m月%d日")       # "2024年01月15日"

# 解析字符串
datetime.strptime("2024-01-15", "%Y-%m-%d")

# 时间计算
tomorrow = today + timedelta(days=1)
next_week = today + timedelta(weeks=1)
diff = datetime(2024, 12, 31) - datetime(2024, 1, 1)
diff.days  # 365

# 时间戳
timestamp = datetime.now().timestamp()
datetime.fromtimestamp(timestamp)

os 和 pathlib

import os
from pathlib import Path

# os 模块
os.getcwd()           # 当前目录
os.listdir(".")       # 列出目录内容
os.path.exists("file.txt")
os.path.isfile("file.txt")
os.path.isdir("folder")
os.makedirs("a/b/c", exist_ok=True)
os.remove("file.txt")
os.rename("old.txt", "new.txt")

# pathlib (推荐，Python 3.4+)
p = Path(".")
p.exists()
p.is_file()
p.is_dir()

# 路径操作
path = Path("/home/user/documents")
path / "file.txt"     # /home/user/documents/file.txt
path.parent           # /home/user
path.name             # documents
path.suffix           # 扩展名

# 遍历文件
for f in Path(".").glob("*.py"):
    print(f)

for f in Path(".").rglob("*.txt"):  # 递归
    print(f)

json 处理

import json

# Python -> JSON
data = {"name": "张三", "age": 25, "skills": ["Python", "Java"]}
json_str = json.dumps(data, ensure_ascii=False, indent=2)

# JSON -> Python
obj = json.loads(json_str)

# 文件操作
with open("data.json", "w", encoding="utf-8") as f:
    json.dump(data, f, ensure_ascii=False, indent=2)

with open("data.json", "r", encoding="utf-8") as f:
    data = json.load(f)

# 自定义序列化
class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

def person_encoder(obj):
    if isinstance(obj, Person):
        return {"name": obj.name, "age": obj.age}
    raise TypeError(f"Object of type {type(obj)} is not JSON serializable")

json.dumps(Person("张三", 25), default=person_encoder)

re 正则表达式

import re

text = "我的邮箱是 test@example.com，电话是 13800138000"

# 匹配
pattern = r"\d+"
match = re.search(pattern, text)
if match:
    print(match.group())  # 13800138000

# 查找所有
re.findall(r"\d+", text)  # ['13800138000']

# 替换
re.sub(r"\d+", "***", text)  # 数字替换为 ***

# 分割
re.split(r"[,，\s]+", "a, b，c d")  # ['a', 'b', 'c', 'd']

# 编译正则 (提高效率)
email_pattern = re.compile(r"[\w.+-]+@[\w-]+\.[\w.-]+")
emails = email_pattern.findall(text)

# 命名组
pattern = r"(?P<name>\w+)@(?P<domain>[\w.]+)"
match = re.search(pattern, "test@example.com")
match.group("name")    # "test"
match.group("domain")  # "example.com"

类型提示 (Type Hints) {.cols-2}

基本类型提示

# 变量类型提示
name: str = "张三"
age: int = 25
price: float = 99.99
is_valid: bool = True

# 函数类型提示
def greet(name: str) -> str:
    return f"Hello, {name}!"

def add(a: int, b: int) -> int:
    return a + b

# 可选类型
from typing import Optional

def get_user(user_id: int) -> Optional[str]:
    # 可能返回 str 或 None
    return None

# Union 类型
from typing import Union

def process(value: Union[int, str]) -> str:
    return str(value)

# Python 3.10+ 可以用 | 代替 Union
def process(value: int | str) -> str:
    return str(value)

复杂类型提示

from typing import List, Dict, Tuple, Set, Callable, Any

# 容器类型
names: List[str] = ["张三", "李四"]
scores: Dict[str, int] = {"math": 90, "english": 85}
point: Tuple[int, int] = (10, 20)
ids: Set[int] = {1, 2, 3}

# Python 3.9+ 可以直接使用内置类型
names: list[str] = ["张三", "李四"]
scores: dict[str, int] = {"math": 90}

# 可调用类型
def apply(func: Callable[[int, int], int], a: int, b: int) -> int:
    return func(a, b)

# Any 类型 (任意类型)
def log(message: Any) -> None:
    print(message)

# 泛型
from typing import TypeVar, Generic

T = TypeVar("T")

class Stack(Generic[T]):
    def __init__(self) -> None:
        self.items: List[T] = []

    def push(self, item: T) -> None:
        self.items.append(item)

    def pop(self) -> T:
        return self.items.pop()

类型别名

from typing import List, Dict, Tuple

# 类型别名
Vector = List[float]
Matrix = List[List[float]]
UserInfo = Dict[str, str | int]

def scale(vector: Vector, factor: float) -> Vector:
    return [x * factor for x in vector]

# TypedDict (Python 3.8+)
from typing import TypedDict

class User(TypedDict):
    name: str
    age: int
    email: str

def create_user(data: User) -> None:
    print(f"Creating user: {data['name']}")

# Literal 类型
from typing import Literal

def set_mode(mode: Literal["read", "write", "append"]) -> None:
    print(f"Mode: {mode}")

set_mode("read")   # OK
# set_mode("edit")  # 类型检查器会报错

实用技巧 {.cols-2}

解包技巧

# 列表解包
a, b, c = [1, 2, 3]
first, *rest = [1, 2, 3, 4, 5]  # first=1, rest=[2,3,4,5]
*head, last = [1, 2, 3, 4, 5]   # head=[1,2,3,4], last=5
a, *middle, z = [1, 2, 3, 4, 5] # middle=[2,3,4]

# 字典解包
d1 = {"a": 1, "b": 2}
d2 = {"c": 3, "d": 4}
merged = {**d1, **d2}  # {"a": 1, "b": 2, "c": 3, "d": 4}

# 函数参数解包
def func(a, b, c):
    return a + b + c

args = [1, 2, 3]
func(*args)  # 6

kwargs = {"a": 1, "b": 2, "c": 3}
func(**kwargs)  # 6

# 交换变量
x, y = y, x

常用内置函数

# 数学相关
abs(-5)         # 5
max(1, 2, 3)    # 3
min(1, 2, 3)    # 1
sum([1, 2, 3])  # 6
pow(2, 3)       # 8
round(3.14159, 2)  # 3.14

# 序列相关
len([1, 2, 3])  # 3
sorted([3, 1, 2])  # [1, 2, 3]
reversed([1, 2, 3])  # 迭代器
enumerate(["a", "b"])  # [(0, "a"), (1, "b")]
zip([1, 2], ["a", "b"])  # [(1, "a"), (2, "b")]

# 函数式编程
list(map(str, [1, 2, 3]))  # ["1", "2", "3"]
list(filter(lambda x: x > 0, [-1, 0, 1, 2]))  # [1, 2]
all([True, True, False])  # False
any([True, False, False])  # True

# 类型转换
int("42")       # 42
float("3.14")   # 3.14
str(42)         # "42"
list("abc")     # ["a", "b", "c"]
tuple([1, 2])   # (1, 2)
set([1, 1, 2])  # {1, 2}
dict([("a", 1)])  # {"a": 1}

性能优化技巧

# 使用生成器代替列表 (节省内存)
# 不好
squares = [x**2 for x in range(1000000)]
# 好
squares = (x**2 for x in range(1000000))

# 字符串拼接
# 不好
s = ""
for item in items:
    s += str(item)
# 好
s = "".join(str(item) for item in items)

# 成员检查用 set
# 不好
if item in large_list:  # O(n)
    pass
# 好
if item in large_set:   # O(1)
    pass

# 使用 collections.deque 做队列
from collections import deque
queue = deque()
queue.append(1)     # O(1)
queue.appendleft(0) # O(1)
queue.pop()         # O(1)
queue.popleft()     # O(1)

# 使用 lru_cache 缓存
from functools import lru_cache

@lru_cache(maxsize=128)
def fibonacci(n):
    if n < 2:
        return n
    return fibonacci(n-1) + fibonacci(n-2)

调试技巧

# 使用 print 调试
print(f"DEBUG: {variable=}")  # Python 3.8+

# 使用 pdb 调试器
import pdb
pdb.set_trace()  # 设置断点

# breakpoint() (Python 3.7+)
breakpoint()

# 查看对象信息
dir(object)      # 列出所有属性和方法
type(object)     # 获取类型
id(object)       # 获取对象 ID
vars(object)     # 获取 __dict__
help(function)   # 查看帮助

# 性能分析
import timeit
timeit.timeit('sum(range(100))', number=10000)

# 使用 logging 代替 print
import logging
logging.basicConfig(level=logging.DEBUG)
logging.debug("调试信息")
logging.info("一般信息")
logging.warning("警告信息")
logging.error("错误信息")